mcpbeat Sign in

Keyword Cluster Architect Agent Skill

> Map 50-200+ keywords into topical clusters for SEO domination. Build content roadmaps for topical authority. "keyword strategy", "content roadmap for SEO", "keyword grouping", "topic clusters", "SEO keyword plan", "map my keywords", "keyword cluster", "hub and spoke content", "build topical authority", "SEO content plan", "keyword universe".

2k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
583
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/Affitor/affiliate-skills --skill keyword-cluster-architect

The instruction itself

21 sections, as written by the author

Keyword Cluster Architect

Map 50-200+ keywords into topical clusters grouped by search intent. Build a content roadmap for dominating a topic with hub-and-spoke architecture. Google rewards topical authority — this skill builds the strategic map that tells you exactly what content to create and in what order.

Stage

S3: Blog & SEO — This is the strategic planning layer FOR blog content. Before writing individual posts, you need a map of the entire keyword landscape organized into clusters.

When to Use

  • User wants to plan SEO content strategy for a niche
  • User asks about keyword research, clustering, or topical authority
  • User says "keyword", "SEO plan", "content roadmap", "topic cluster", "hub and spoke"
  • Before running affiliate-blog-builder — to know WHICH articles to write
  • After monopoly-niche-finder — to map the keyword universe for the winning niche

Input Schema

niche: string                 # REQUIRED — the topic to cluster
                              # e.g., "AI video tools", "email marketing for SaaS"

seed_keywords: string[]       # OPTIONAL — starting keywords to expand from
                              # Default: auto-generated from niche

depth: string                 # OPTIONAL — "quick" (50 keywords) | "standard" (100) | "deep" (200+)
                              # Default: "standard"

affiliate_products: string[]  # OPTIONAL — products you promote (to prioritize commercial keywords)
                              # Default: none

Chaining from S1 monopoly-niche-finder: Use monopoly_niche.intersection as the niche input.

Workflow

Step 1: Generate Seed Keywords

If not provided, generate 5-10 seed keywords from the niche:

  • Product-focused: "[product] review", "best [category]"
  • Problem-focused: "how to [solve problem]", "[problem] solution"
  • Comparison: "[product A] vs [product B]", "alternatives to [product]"
  • Tutorial: "how to use [product]", "[product] tutorial"

Step 2: Expand Keywords

For each seed, use web_search to discover related keywords:

  • Search: "[seed keyword]" — note related searches, People Also Ask
  • Search: "[seed keyword] guide" OR "[seed keyword] tutorial" — informational variants
  • Search: "best [seed keyword]" OR "[seed keyword] review" — commercial variants

Collect 50-200+ unique keywords depending on depth.

Step 3: Classify by Intent

Read shared/references/seo-strategy.md for clustering methodology.

Classify each keyword:

  • Informational (I): Learning, how-to, what-is → blog posts, tutorials
  • Commercial (C): Comparing, evaluating, reviewing → comparison posts, reviews
  • Transactional (T): Ready to buy, pricing, discount → landing pages, deal pages
  • Navigational (N): Brand-specific, login → skip (not your traffic to capture)

Step 4: Cluster by Topic

Group keywords that share the same search intent (would be answered by the same page):

Cluster: "[Main Topic]"
  Type: [I/C/T]
  Hub keyword: [highest volume keyword]
  Supporting keywords:
    - [keyword 1] — [est. volume]
    - [keyword 2] — [est. volume]
  Content type: [blog post / comparison / review / tutorial / landing page]
  Priority: [1-5 based on volume × intent × competition]

Step 5: Build Content Roadmap

Organize clusters into a hub-and-spoke map:

  • Identify the hub page (broadest, highest-volume cluster)
  • Connect spoke pages (specific clusters that link back to hub)
  • Prioritize by: commercial intent first (revenue), then informational (traffic)
  • Estimate effort: number of articles needed, suggested publishing cadence

Step 6: Self-Validation

  • [ ] Clusters are based on actual search data, not guesses
  • [ ] Each cluster has a clear search intent (I, C, or T)
  • [ ] Hub-and-spoke structure is logical (hub is broad, spokes are specific)
  • [ ] Priority ordering makes business sense (revenue-driving content first)
  • [ ] Total content pieces are realistic for user's capacity

Output Schema

output_schema_version: "1.0.0"
keyword_clusters:
  niche: string
  total_keywords: number
  total_clusters: number

  hub:
    keyword: string
    cluster_name: string
    content_type: string
    priority: number

  clusters:
    - name: string
      intent: string          # "informational" | "commercial" | "transactional"
      hub_keyword: string
      keywords: string[]
      content_type: string    # "blog" | "comparison" | "review" | "tutorial" | "landing"
      priority: number        # 1-5
      estimated_volume: string

  content_roadmap:
    total_articles: number
    publishing_cadence: string
    priority_order: string[]  # Cluster names in order to write

  target_keywords: string[]   # Flat list of all keywords for chaining

chain_metadata:
  skill_slug: "keyword-cluster-architect"
  stage: "blog"
  timestamp: string
  suggested_next:
    - "affiliate-blog-builder"
    - "content-moat-calculator"
    - "comparison-post-writer"
    - "landing-page-creator"

Output Format

## Keyword Cluster Map: [Niche]

### Overview
- **Total keywords:** XXX
- **Clusters:** XX
- **Hub topic:** [main hub]
- **Content pieces needed:** XX articles

### Hub & Spoke Map

[HUB: Main Topic]

/ | | \

[Spoke] [Spoke] [Spoke] [Spoke]

| | | |

[Sub] [Sub] [Sub] [Sub]


### Clusters by Priority

#### Priority 1: [Cluster Name] (Commercial Intent)
- **Hub keyword:** [keyword] — [volume]
- **Content type:** [comparison / review]
- **Keywords:** [list]
- **Article idea:** [specific title]

#### Priority 2: [Cluster Name] (Informational Intent)
[same structure]

[Continue for all clusters]

### Content Roadmap
| Week | Cluster | Article | Intent | Priority |
|---|---|---|---|---|
| 1 | [cluster] | [title] | C | 1 |
| 2 | [cluster] | [title] | C | 1 |
| 3 | [cluster] | [title] | I | 2 |

### Next Steps
- Run `content-moat-calculator` to estimate effort for topical authority
- Run `affiliate-blog-builder` for Priority 1 articles
- Run `comparison-post-writer` for commercial clusters

Error Handling

  • Niche too broad: "This niche is very broad. Let me narrow to a sub-niche for more actionable clusters. Or run monopoly-niche-finder first."
  • No search volume: "This niche may be too narrow for significant search traffic. Consider broadening slightly."
  • Too many keywords: Group aggressively into fewer clusters. Quality of clustering > quantity of keywords.
  • No commercial intent keywords: Flag as concern — hard to monetize through affiliate without commercial intent. Suggest adjacent niches.

Examples

Example 1: "Map keywords for AI video tools"

→ Seeds: "best AI video tools", "AI video generator", "HeyGen review". Expand to 100+ keywords. Cluster: "AI video reviews" (C), "how to make AI videos" (I), "AI video pricing" (T), "AI video vs traditional" (C). Hub: "Best AI Video Tools 2025".

Example 2: "Keyword strategy for my affiliate blog about email marketing"

→ Deep keyword research. Clusters: "email marketing platforms" (C), "email automation tutorials" (I), "email marketing pricing comparison" (T), "email deliverability guides" (I).

Example 3: "Plan my content roadmap" (after monopoly-niche-finder)

→ Pick up niche from chain. Map 100+ keywords in that intersection niche. Prioritize clusters by revenue potential.

Flywheel Connections

Feeds Into

  • affiliate-blog-builder (S3) — which articles to write and target keywords
  • comparison-post-writer (S3) — commercial clusters become comparison articles
  • content-moat-calculator (S3) — keyword count informs moat estimation
  • landing-page-creator (S4) — transactional clusters become landing pages
  • internal-linking-optimizer (S6) — cluster structure defines link architecture

Fed By

  • monopoly-niche-finder (S1) — niche to cluster keywords for
  • content-pillar-atomizer (S2) — content pillars suggest keyword areas
  • seo-audit (S6) — current ranking data reveals keyword gaps

Feedback Loop

  • seo-audit (S6) reveals ranking gaps in existing clusters → add keywords and new content to fill gaps

Quality Gate

Before delivering output, verify:

  • Would I share this on MY personal social?
  • Contains specific, surprising detail? (not generic)
  • Respects reader's intelligence?
  • Remarkable enough to share? (Purple Cow test)
  • Irresistible offer framing? (roadmap feels actionable)

Any NO → rewrite before delivering.

References

  • shared/references/seo-strategy.md — Topical authority, clustering methodology, hub-and-spoke
  • shared/references/affiliate-glossary.md — Terminology
  • shared/references/flywheel-connections.md — Master connection map

Other skills for the same job

different authors, same section of the catalogue
Internal Comms
by anthropics
vendor ×13

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

6k tokens
Competitive Ads Extractor
by frostant
×10

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.

2k tokens
Lead Research Assistant
by frostant
×8

Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.

2k tokens
Developer Growth Analysis
by frostant
×6

Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.

4k tokens
App Store Optimization
by alirezarezvani
×3

Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store

55k tokens scripts
Deeptools
by christophacham
×3

NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.

21k tokens scripts
Pymatgen
by christophacham
×3

Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.

26k tokens scripts
Enhance Prompt
by google-labs-code
vendor ×2

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

3k tokens

How to use it

Copy the folder

Take affitor/keyword-cluster-architect from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.